{"title":"基于光致铁电退极化的光电晶体管光电去耦在传感器内计算中的应用","authors":"Guangcheng Wu, Fenghao Yu, Jiali Yi, Huawei Liu, Xiulian Fan, Cheng Li, Chenguang Zhu, Xingxia Sun, Yong Liu, Qin Shuai, Tanghao Xie, Shengman Li, Yu Zhou, Dong Li, Anlian Pan","doi":"10.1021/acsnano.5c04090","DOIUrl":null,"url":null,"abstract":"Highly sensitive sensors are critical for in-sensor computing, an ultrafast and low-power machine vision technology. However, capturing sharp images without motion blur in low-light and high-speed situations remains challenging due to weak photoresponse. Here, we present a heterostructure ferroelectric phototransistor leveraging opto-electrical decoupling for fast perception and in-sensor computing. The channel is preprogrammed to a low-resistance state via ferroelectric polarization, while light modulates the drain current through light-induced ferroelectric depolarization. This mechanism enables a record-high MoTe<sub>2</sub>-based photoresponsivity of 3.05×10<sup>4</sup> A/W by optimizing the balance between depolarization and screening fields. The sensors can perceive light pulses as short as 200 μs, achieving an operating frequency of 5 kHz and an energy consumption of 74 fJ. Utilizing a light-programmable neutral point, a 3 × 3 sensor array was developed as the optical kernel for scene-specific in-sensor computing, achieving a license plate recognition accuracy of 92.4% with significantly reduced motion blur. These results demonstrate the potential of this technology for high-speed, low-light machine vision applications.","PeriodicalId":21,"journal":{"name":"ACS Nano","volume":"16 1","pages":""},"PeriodicalIF":16.0000,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Opto-Electrical Decoupling of Phototransistors via Light-Induced Ferroelectric Depolarization for In-Sensor Computing\",\"authors\":\"Guangcheng Wu, Fenghao Yu, Jiali Yi, Huawei Liu, Xiulian Fan, Cheng Li, Chenguang Zhu, Xingxia Sun, Yong Liu, Qin Shuai, Tanghao Xie, Shengman Li, Yu Zhou, Dong Li, Anlian Pan\",\"doi\":\"10.1021/acsnano.5c04090\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Highly sensitive sensors are critical for in-sensor computing, an ultrafast and low-power machine vision technology. However, capturing sharp images without motion blur in low-light and high-speed situations remains challenging due to weak photoresponse. Here, we present a heterostructure ferroelectric phototransistor leveraging opto-electrical decoupling for fast perception and in-sensor computing. The channel is preprogrammed to a low-resistance state via ferroelectric polarization, while light modulates the drain current through light-induced ferroelectric depolarization. This mechanism enables a record-high MoTe<sub>2</sub>-based photoresponsivity of 3.05×10<sup>4</sup> A/W by optimizing the balance between depolarization and screening fields. The sensors can perceive light pulses as short as 200 μs, achieving an operating frequency of 5 kHz and an energy consumption of 74 fJ. Utilizing a light-programmable neutral point, a 3 × 3 sensor array was developed as the optical kernel for scene-specific in-sensor computing, achieving a license plate recognition accuracy of 92.4% with significantly reduced motion blur. These results demonstrate the potential of this technology for high-speed, low-light machine vision applications.\",\"PeriodicalId\":21,\"journal\":{\"name\":\"ACS Nano\",\"volume\":\"16 1\",\"pages\":\"\"},\"PeriodicalIF\":16.0000,\"publicationDate\":\"2025-05-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Nano\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://doi.org/10.1021/acsnano.5c04090\",\"RegionNum\":1,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Nano","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1021/acsnano.5c04090","RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
摘要
高灵敏度传感器对于传感器内计算(一种超快、低功耗的机器视觉技术)至关重要。然而,由于光响应弱,在低光和高速情况下捕捉没有运动模糊的清晰图像仍然具有挑战性。在这里,我们提出了一种利用光电去耦的异质结构铁电光电晶体管,用于快速感知和传感器内计算。该通道通过铁电极化预编程为低电阻状态,而光通过光诱导铁电去极化调制漏极电流。该机制通过优化退极化和筛选场之间的平衡,使mote2基光响应率达到创纪录的3.05×104 a /W。该传感器可感知短至200 μs的光脉冲,工作频率为5 kHz,功耗为74 fJ。利用光可编程中性点,开发了一个3 × 3传感器阵列作为光学内核,用于特定场景的传感器内计算,实现了92.4%的车牌识别精度,显著降低了运动模糊。这些结果证明了该技术在高速、低光机器视觉应用中的潜力。
Opto-Electrical Decoupling of Phototransistors via Light-Induced Ferroelectric Depolarization for In-Sensor Computing
Highly sensitive sensors are critical for in-sensor computing, an ultrafast and low-power machine vision technology. However, capturing sharp images without motion blur in low-light and high-speed situations remains challenging due to weak photoresponse. Here, we present a heterostructure ferroelectric phototransistor leveraging opto-electrical decoupling for fast perception and in-sensor computing. The channel is preprogrammed to a low-resistance state via ferroelectric polarization, while light modulates the drain current through light-induced ferroelectric depolarization. This mechanism enables a record-high MoTe2-based photoresponsivity of 3.05×104 A/W by optimizing the balance between depolarization and screening fields. The sensors can perceive light pulses as short as 200 μs, achieving an operating frequency of 5 kHz and an energy consumption of 74 fJ. Utilizing a light-programmable neutral point, a 3 × 3 sensor array was developed as the optical kernel for scene-specific in-sensor computing, achieving a license plate recognition accuracy of 92.4% with significantly reduced motion blur. These results demonstrate the potential of this technology for high-speed, low-light machine vision applications.
期刊介绍:
ACS Nano, published monthly, serves as an international forum for comprehensive articles on nanoscience and nanotechnology research at the intersections of chemistry, biology, materials science, physics, and engineering. The journal fosters communication among scientists in these communities, facilitating collaboration, new research opportunities, and advancements through discoveries. ACS Nano covers synthesis, assembly, characterization, theory, and simulation of nanostructures, nanobiotechnology, nanofabrication, methods and tools for nanoscience and nanotechnology, and self- and directed-assembly. Alongside original research articles, it offers thorough reviews, perspectives on cutting-edge research, and discussions envisioning the future of nanoscience and nanotechnology.